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Generating protein folding trajectories using contact-map-driven directed walks
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Fakhoury, Ziad, Sosso, Gabriele C. and Habershon, Scott (2023) Generating protein folding trajectories using contact-map-driven directed walks. Journal of Chemical Information and Modeling, 63 (7). pp. 2181-2195. doi:10.1021/acs.jcim.3c00023 ISSN 1549-960x.
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Official URL: https://doi.org/10.1021/acs.jcim.3c00023
Abstract
Recent advances in machine learning methods have had a significant impact on protein structure prediction, but accurate generation and characterization of protein-folding pathways remains intractable. Here, we demonstrate how protein folding trajectories can be generated using a directed walk strategy operating in the space defined by the residue-level contact-map. This double-ended strategy views protein folding as a series of discrete transitions between connected minima on the potential energy surface. Subsequent reaction-path analysis for each transition enables thermodynamic and kinetic characterization of each protein-folding path. We validate the protein-folding paths generated by our discretized-walk strategy against direct molecular dynamics simulations for a series of model coarse-grained proteins constructed from hydrophobic and polar residues. This comparison demonstrates that ranking discretized paths based on the intermediate energy barriers provides a convenient route to identifying physically sensible folding ensembles. Importantly, by using directed walks in the protein contact-map space, we circumvent several of the traditional challenges associated with protein-folding studies, namely, long time scales required and the choice of a specific order parameter to drive the folding process. As such, our approach offers a useful new route for studying the protein-folding problem.
Item Type: | Journal Article | ||||||||
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Subjects: | Q Science > QD Chemistry | ||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Chemistry | ||||||||
SWORD Depositor: | Library Publications Router | ||||||||
Journal or Publication Title: | Journal of Chemical Information and Modeling | ||||||||
Publisher: | American Chemical Society | ||||||||
ISSN: | 1549-960x | ||||||||
Official Date: | 10 April 2023 | ||||||||
Dates: |
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Volume: | 63 | ||||||||
Number: | 7 | ||||||||
Page Range: | pp. 2181-2195 | ||||||||
DOI: | 10.1021/acs.jcim.3c00023 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||
Date of first compliant deposit: | 28 April 2023 | ||||||||
Date of first compliant Open Access: | 28 April 2023 | ||||||||
RIOXX Funder/Project Grant: |
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